Graph Convolutional Networks Embedding Textual Structure Information for Relation Extraction

Deep neural network-based relational extraction research has made significant progress in recent years,andit provides data support for many natural language processing downstream tasks such as building knowledgegraph,sentiment analysis and question-answering systems.However,previous studies ignored much unusedstructural information in sentences that could enhance the performance of the relation extraction task.Moreover,most existing dependency-based models utilize self-attention to distinguish the importance of context,whichhardly deals withmultiple-structure information.To efficiently leverage multiple structure information,this paperproposes a dynamic structure attention mechanism model based on textual structure information,which deeplyintegrates word embedding,named entity recognition labels,part of speech,dependency tree and dependency typeinto a graph convolutional network.Specifically,our model extracts text features of different structures from theinput sentence.Textual Structure information Graph Convolutional Networks employs the dynamic structureattention mechanism to learn multi-structure attention,effectively distinguishing important contextual features invarious structural information.In addition,multi-structure weights are carefully designed as amergingmechanismin the different structure attention to dynamically adjust the final attention.This paper combines these featuresand trains a graph convolutional network for relation extraction.We experiment on supervised relation extractiondatasets including SemEval 2010 Task 8,TACRED,TACREV,and Re-TACED,the result significantly outperformsthe previous.

From text to image:challenges in integrating vision into ChatGPT for medical image interpretation

Large language models(LLMs),such as ChatGPT developed by OpenAI,represent a significant advancement in artificial intelligence(AI),designed to understand,generate,and interpret human language by analyzing extensive text data.Their potential integration into clinical settings offers a promising avenue that could transform clinical diagnosis and decision-making processes in the future(Thirunavukarasu et al.,2023).This article aims to provide an in-depth analysis of LLMs’current and potential impact on clinical practices.Their ability to generate differential diagnosis lists underscores their potential as invaluable tools in medical practice and education(Hirosawa et al.,2023;Koga et al.,2023).

Viscosity and structure relationship with equimolar substitution of CaO with MgO in the CaO–MgO–Al_(2)O_(3)–SiO_(2)slag melts

Currently,the Al_(2)O_(3)content in the high-alumina slag systems within blast furnaces is generally limited to 16wt%–18.5wt%,making it challenging to overcome this limitation.Unlike most studies that concentrated on managing the MgO/Al_(2)O_(3)ratio or basicity,this paper explored the effect of equimolar substitution of MgO for CaO on the viscosity and structure of a high-alumina CaO-MgO-Al_(2)O_(3)-SiO_(2)slag system,providing theoretical guidance and data to facilitate the application of high-alumina ores.The results revealed that the viscosity first decreased and then increased with higher MgO substitution,reaching a minimum at 15mol%MgO concentration.Fourier transform infrared spectroscopy(FTIR)results found that the depths of the troughs representing[SiO_(4)]tetrahedra,[AlO_(4)]tetrahedra,and Si-O-Al bending became progressively deeper with increased MgO substitution.Deconvolution of the Raman spectra showed that the average number of bridging oxygens per Si atom and the X_(Q^(3))/X_(Q^(2))(X_(Q^(i))is the molar fraction of Q^(i) unit,and i is the number of bridging oxygens in a[SiO_(4)]tetrahedral unit)ratio increased from 2.30 and 1.02 to 2.52 and 2.14,respectively,indicating a progressive polymerization of the silicate structure.X-ray photoelectron spectroscopy(XPS)results highlighted that non-bridging oxygen content decreased from 77.97mol% to 63.41mol% with increasing MgO concentration,whereas bridging oxygen and free oxygen contents increased.Structural analysis demonstrated a gradual increase in the polymerization degree of the tetrahedral structure with the increase in MgO substitution.However,bond strength is another important factor affecting the slag viscosity.The occurrence of a viscosity minimum can be attributed to the complex evolution of bond strengths of non-bridging oxygens generated during depolymerization of the[SiO_(4)]and[AlO_(4)]tetrahedral structures by CaO and MgO.

Optimizing electronic structure through point defect engineering for enhanced electrocatalytic energy conversion

Point defect engineering endows catalysts with novel physical and chemical properties,elevating their electrocatalytic efficiency.The introduction of defects emerges as a promising strategy,effectively modifying the electronic structure of active sites.This optimization influences the adsorption energy of intermediates,thereby mitigating reaction energy barriers,altering paths,enhancing selectivity,and ultimately improving the catalytic efficiency of electrocatalysts.To elucidate the impact of defects on the electrocatalytic process,we comprehensively outline the roles of various point defects,their synthetic methodologies,and characterization techniques.Importantly,we consolidate insights into the relationship between point defects and catalytic activity for hydrogen/oxygen evolution and CO_(2)/O_(2)/N_(2) reduction reactions by integrating mechanisms from diverse reactions.This underscores the pivotal role of point defects in enhancing catalytic performance.At last,the principal challenges and prospects associated with point defects in current electrocatalysts are proposed,emphasizing their role in advancing the efficiency of electrochemical energy storage and conversion materials.

Advanced Functional Electromagnetic Shielding Materials:A Review Based on Micro‑Nano Structure Interface Control of Biomass Cell Walls

Research efforts on electromagnetic interference(EMI)shielding materials have begun to converge on green and sustainable biomass materials.These materials offer numerous advantages such as being lightweight,porous,and hierarchical.Due to their porous nature,interfacial compatibility,and electrical conductivity,biomass materials hold significant potential as EMI shielding materials.Despite concerted efforts on the EMI shielding of biomass materials have been reported,this research area is still relatively new compared to traditional EMI shielding materials.In particular,a more comprehensive study and summary of the factors influencing biomass EMI shielding materials including the pore structure adjustment,preparation process,and micro-control would be valuable.The preparation methods and characteristics of wood,bamboo,cellulose and lignin in EMI shielding field are critically discussed in this paper,and similar biomass EMI materials are summarized and analyzed.The composite methods and fillers of various biomass materials were reviewed.this paper also highlights the mechanism of EMI shielding as well as existing prospects and challenges for development trends in this field.

Molecular Structure Tailoring of Organic Spacers for High‑Performance Ruddlesden–Popper Perovskite Solar Cells

Layer-structured Ruddlesden–Popper(RP)perovskites(RPPs)with decent stability have captured the imagination of the photovoltaic research community and bring hope for boosting the development of perovskite solar cell(PSC)technology.However,two-dimensional(2D)or quasi-2D RP PSCs are encountered with some challenges of the large exciton binding energy,blocked charge transport and poor film quality,which restrict their photovoltaic performance.Fortunately,these issues can be readily resolved by rationally designing spacer cations of RPPs.This review mainly focuses on how to design the molecular structures of organic spacers and aims to endow RPPs with outstanding photovoltaic applications.We firstly elucidated the important roles of organic spacers in impacting crystallization kinetics,charge transporting ability and stability of RPPs.Then we brought three aspects to attention for designing organic spacers.Finally,we presented the specific molecular structure design strategies for organic spacers of RPPs aiming to improve photovoltaic performance of RP PSCs.These proposed strategies in this review will provide new avenues to develop novel organic spacers for RPPs and advance the development of RPP photovoltaic technology for future applications.

3D Printing of Tough Hydrogel Scaffolds with Functional Surface Structures for Tissue Regeneration

Hydrogel scaffolds have numerous potential applications in the tissue engineering field.However,tough hydrogel scaffolds implanted in vivo are seldom reported because it is difficult to balance biocompatibility and high mechanical properties.Inspired by Chinese ramen,we propose a universal fabricating method(printing-P,training-T,cross-linking-C,PTC&PCT)for tough hydrogel scaffolds to fill this gap.First,3D printing fabricates a hydrogel scaffold with desired structures(P).Then,the scaffold could have extraordinarily high mechanical properties and functional surface structure by cycle mechanical training with salting-out assistance(T).Finally,the training results are fixed by photo-cross-linking processing(C).The tough gelatin hydrogel scaffolds exhibit excellent tensile strength of 6.66 MPa(622-fold untreated)and have excellent biocompatibility.Furthermore,this scaffold possesses functional surface structures from nanometer to micron to millimeter,which can efficiently induce directional cell growth.Interestingly,this strategy can produce bionic human tissue with mechanical properties of 10 kPa-10 MPa by changing the type of salt,and many hydrogels,such as gelatin and silk,could be improved with PTC or PCT strategies.Animal experiments show that this scaffold can effectively promote the new generation of muscle fibers,blood vessels,and nerves within 4 weeks,prompting the rapid regeneration of large-volume muscle loss injuries.

Graphene Aerogel Composites with Self‑Organized Nanowires‑Packed Honeycomb Structure for Highly Efficient Electromagnetic Wave Absorption

With vigorous developments in nanotechnology,the elaborate regulation of microstructure shows attractive potential in the design of electromagnetic wave absorbers.Herein,a hierarchical porous structure and composite heterogeneous interface are constructed successfully to optimize the electromagnetic loss capacity.The macro–micro-synergistic graphene aerogel formed by the ice template‑assisted 3D printing strategy is cut by silicon carbide nanowires(SiC_(nws))grown in situ,while boron nitride(BN)interfacial structure is introduced on graphene nanoplates.The unique composite structure forces multiple scattering of incident EMWs,ensuring the combined effects of interfacial polarization,conduction networks,and magnetic-dielectric synergy.Therefore,the as-prepared composites present a minimum reflection loss value of−37.8 dB and a wide effective absorption bandwidth(EAB)of 9.2 GHz(from 8.8 to 18.0 GHz)at 2.5 mm.Besides,relying on the intrinsic high-temperature resistance of SiC_(nws) and BN,the EAB also remains above 5.0 GHz after annealing in air environment at 600℃ for 10 h.

Understanding the local structure and thermophysical behavior of Mg-La liquid alloys via machine learning potential

The local structure and thermophysical behavior of Mg-La liquid alloys were in-depth understood using deep potential molecular dynamic(DPMD) simulation driven via machine learning to promote the development of Mg-La alloys. The robustness of the trained deep potential(DP) model was thoroughly evaluated through several aspects, including root-mean-square errors(RMSEs), energy and force data, and structural information comparison results;the results indicate the carefully trained DP model is reliable. The component and temperature dependence of the local structure in the Mg-La liquid alloy was analyzed. The effect of Mg content in the system on the first coordination shell of the atomic pairs is the same as that of temperature. The pre-peak demonstrated in the structure factor indicates the presence of a medium-range ordered structure in the Mg-La liquid alloy, which is particularly pronounced in the 80at% Mg system and disappears at elevated temperatures. The density, self-diffusion coefficient, and shear viscosity for the Mg-La liquid alloy were predicted via DPMD simulation, the evolution patterns with Mg content and temperature were subsequently discussed, and a database was established accordingly. Finally, the mixing enthalpy and elemental activity of the Mg-La liquid alloy at 1200 K were reliably evaluated,which provides new guidance for related studies.

Copper complexes of anthrahydrazone bearing pyridyl side chain:Synthesis,crystal structure,anticancer activity,and DNA binding

To expand the study on the structures and biological activities of the anthracyclines anticancer drugs and reduce their toxic side effects,the new anthraquinone derivatives,9‑pyridylanthrahydrazone(9‑PAH)and 9,10‑bispyridylanthrahydrazone(9,10‑PAH)were designed and synthesized.Utilizing 9‑PAH and 9,10‑PAH as promising anticancer ligands,their respective copper complexes,namely[Cu(L1)Cl_(2)]Cl(1)and{[Cu_(4)(μ_(2)‑Cl)_(3)Cl_(4)(9,10‑PAH)_(2)(DMSO)_(2)]Cl_(2)}_(n)(2),were subsequently synthesized,where the new ligand L1 is formed by coupling two 9‑PAH ligands in the coordination reaction.The chemical and crystal structures of 1 and 2 were elucidated by IR,MS,elemental analysis,and single‑crystal X‑ray diffraction.Complex 1 forms a mononuclear structure.L1 coordinates with Cu through its three N atoms,together with two Cl atoms,to form a five‑coordinated square pyramidal geometry.Complex 2 constitutes a polymeric structure,wherein each structural unit centrosymmetrically encompasses two five‑coordinated binuclear copper complexes(Cu1,Cu2)of 9,10‑PAH,with similar square pyramidal geometry.A chlorine atom(Cl_(2)),located at the symmetry center,bridges Cu1 and Cu1A to connect the two binuclear copper structures.Meanwhile,the two five‑coordinated Cu2 atoms symmetrically bridge the adjacent structural units via one coordinated Cl atom,respectively,thus forming a 1D chain‑like polymeric structure.In vitro anticancer activity assessments revealed that 1 and 2 showed significant cytotoxicity even higher than cisplatin.Specifically,the IC_(50)values of 2 against HeLa‑229 and SK‑OV‑3 cancer cell lines were determined to be(5.92±0.32)μmol·L^(-1)and(6.48±0.39)μmol·L^(-1),respectively.2 could also block the proliferation of HeLa‑229 cells in S phase and significantly induce cell apoptosis.In addition,fluorescence quenching competition experiments suggested that 2 might interact with DNA by an intercalative binding mode,offering insights into its underlying anticancer mechanism.CCDC:2388918,1;2388919,2.

Emerging structures and dynamic mechanisms ofγ-secretase for Alzheimer’s disease

γ-Secretase,called“the proteasome of the membrane,”is a membrane-embedded protease complex that cleaves 150+peptide substrates with central roles in biology and medicine,including amyloid precursor protein and the Notch family of cell-surface receptors.Mutations inγ-secretase and amyloid precursor protein lead to early-onset familial Alzheimer’s disease.γ-Secretase has thus served as a critical drug target for treating familial Alzheimer’s disease and the more common late-onset Alzheimer’s disease as well.However,critical gaps remain in understanding the mechanisms of processive proteolysis of substrates,the effects of familial Alzheimer’s disease mutations,and allosteric modulation of substrate cleavage byγ-secretase.In this review,we focus on recent studies of structural dynamic mechanisms ofγ-secretase.Different mechanisms,including the“Fit-Stay-Trim,”“Sliding-Unwinding,”and“Tilting-Unwinding,”have been proposed for substrate proteolysis of amyloid precursor protein byγ-secretase based on all-atom molecular dynamics simulations.While an incorrect registry of the Notch1 substrate was identified in the cryo-electron microscopy structure of Notch1-boundγ-secretase,molecular dynamics simulations on a resolved model of Notch1-boundγ-secretase that was reconstructed using the amyloid precursor protein-boundγ-secretase as a template successfully capturedγ-secretase activation for proper cleavages of both wildtype and mutant Notch,being consistent with biochemical experimental findings.The approach could be potentially applied to decipher the processing mechanisms of various substrates byγ-secretase.In addition,controversy over the effects of familial Alzheimer’s disease mutations,particularly the issue of whether they stabilize or destabilizeγ-secretase-substrate complexes,is discussed.Finally,an outlook is provided for future studies ofγ-secretase,including pathways of substrate binding and product release,effects of modulators on familial Alzheimer’s disease mutations of theγ-secretase-substrate complexes.Comprehensive understanding of the functional mechanisms ofγ-secretase will greatly facilitate the rational design of effective drug molecules for treating familial Alzheimer’s disease and perhaps Alzheimer’s disease in general.

Designing Electronic Structures of Multiscale Helical Converters for Tailored Ultrabroad Electromagnetic Absorption

Atomic-scale doping strategies and structure design play pivotal roles in tailoring the electronic structure and physicochemical property of electromagnetic wave absorption(EMWA)materials.However,the relationship between configuration and electromagnetic(EM)loss mechanism has remained elusive.Herein,drawing inspiration from the DNA transcription process,we report the successful synthesis of novel in situ Mn/N co-doped helical carbon nanotubes with ultrabroad EMWA capability.Theoretical calculation and EM simulation confirm that the orbital coupling and spin polarization of the Mn–N4–C configuration,along with cross polarization generated by the helical structure,endow the helical converters with enhanced EM loss.As a result,HMC-8 demonstrates outstanding EMWA performance,achieving a minimum reflection loss of−63.13 dB at an ultralow thickness of 1.29 mm.Through precise tuning of the graphite domain size,HMC-7 achieves an effective absorption bandwidth(EAB)of 6.08 GHz at 2.02 mm thickness.Furthermore,constructing macroscale gradient metamaterials enables an ultrabroadband EAB of 12.16 GHz at a thickness of only 5.00 mm,with the maximum radar cross section reduction value reaching 36.4 dB m2.This innovative approach not only advances the understanding of metal–nonmetal co-doping but also realizes broadband EMWA,thus contributing to the development of EMWA mechanisms and applications.

Experimental investigation on the anti-detonation performance of composite structure containing foam geopolymer backfill material

The compression and energy absorption properties of foam geopolymers increase stress wave attenuation under explosion impacts,reducing the vibration effect on the structure.Explosion tests were conducted using several composite structure models,including a concrete lining structure(CLS)without foam geopolymer and six foam geopolymer composite structures(FGCS)with different backfill parameters,to study the dynamic response and wave dissipation mechanisms of FGCS under explosive loading.Pressure,strain,and vibration responses at different locations were synchronously tested.The damage modes and dynamic responses of different models were compared,and how wave elimination and energy absorption efficiencies were affected by foam geopolymer backfill parameters was analyzed.The results showed that the foam geopolymer absorbed and dissipated the impact energy through continuous compressive deformation under high strain rates and dynamic loading,reducing the strain in the liner structure by 52%and increasing the pressure attenuation rate by 28%.Additionally,the foam geopolymer backfill reduced structural vibration and liner deformation,with the FGCS structure showing 35%less displacement and 70%less acceleration compared to the CLS.The FGCS model with thicker,less dense foam geopolymer backfill,having more pores and higher porosity,demonstrated better compression and energy absorption under dynamic impact,increasing stress wave attenuation efficiency.By analyzing the stress wave propagation and the compression characteristics of the porous medium,it was concluded that the stress transfer ratio of FGCS-ρ-579 was 77%lower than that of CLS,and the transmitted wave energy was 90%lower.The results of this study provide a scientific basis for optimizing underground composite structure interlayer parameters.

Honeycomb-spiderweb-inspired self-similar hybrid cellular structures for impact applications

Inspired by nature's self-similar designs,novel honeycomb-spiderweb based self-similar hybrid cellular structures are proposed here for efficient energy absorption in impact applications.The energy absorption is enhanced by optimizing the geometry and topology for a given mass.The proposed hybrid cellular structure is arrived after a thorough analysis of topologically enhanced self-similar structures.The optimized cell designs are rigorously tested considering dynamic loads involving crush and high-velocity bullet impact.Furthermore,the influence of thickness,radial connectivity,and order of patterning at the unit cell level are also investigated.The maximum crushing efficiency attained is found to be more than 95%,which is significantly higher than most existing traditional designs.Later on,the first and second-order hierarchical self-similar unit cell designs developed during crush analysis are used to prepare the cores for sandwich structures.Impact tests are performed on the developed sandwich structures using the standard 9-mm parabellum.The influence of multistaging on impact resistance is also investigated by maintaining a constant total thickness and mass of the sandwich structure.Moreover,in order to avoid layer-wise weak zones and hence,attain a uniform out-of-plane impact strength,off-setting the designs in each stage is proposed.The sandwich structures with first and second-order self-similar hybrid cores are observed to withstand impact velocities as high as 170 m/s and 270 m/s,respectively.

Subsurface Temperature and Salinity Structures Inversion Using a Stacking-Based Fusion Model from Satellite Observations in the South China Sea

Three-dimensional ocean subsurface temperature and salinity structures(OST/OSS)in the South China Sea(SCS)play crucial roles in oceanic climate research and disaster mitigation.Traditionally,real-time OST and OSS are mainly obtained through in-situ ocean observations and simulation by ocean circulation models,which are usually challenging and costly.Recently,dynamical,statistical,or machine learning models have been proposed to invert the OST/OSS from sea surface information;however,these models mainly focused on the inversion of monthly OST and OSS.To address this issue,we apply clustering algorithms and employ a stacking strategy to ensemble three models(XGBoost,Random Forest,and LightGBM)to invert the real-time OST/OSS based on satellite-derived data and the Argo dataset.Subsequently,a fusion of temperature and salinity is employed to reconstruct OST and OSS.In the validation dataset,the depth-averaged Correlation(Corr)of the estimated OST(OSS)is 0.919(0.83),and the average Root-Mean-Square Error(RMSE)is0.639°C(0.087 psu),with a depth-averaged coefficient of determination(R~2)of 0.84(0.68).Notably,at the thermocline where the base models exhibit their maximum error,the stacking-based fusion model exhibited significant performance enhancement,with a maximum enhancement in OST and OSS inversion exceeding 10%.We further found that the estimated OST and OSS exhibit good agreement with the HYbrid Coordinate Ocean Model(HYCOM)data and BOA_Argo dataset during the passage of a mesoscale eddy.This study shows that the proposed model can effectively invert the real-time OST and OSS,potentially enhancing the understanding of multi-scale oceanic processes in the SCS.

Rapid post-earthquake safety assessment of low-rise reinforced concrete structures

Many countries throughout the world have experienced large earthquakes,which cause building damage or collapse.After such earthquakes,structures must be inspected rapidly to judge whether they are safe to reoccupy.To facilitate the inspection process,the authors previously developed a rapid building safety assessment system using sparse acceleration measurements for steel framed buildings.The proposed system modeled nonlinearity in the measurement data using a calibrated simplified lumped-mass model and convolutional neural networks(CNNs),based on which the buildinglevel damage index was estimated rapidly after earthquakes.The proposed system was validated for a nonlinear 3D numerical model of a five-story steel building,and later for a large-scale specimen of an 18-story building in Japan tested on the E-Defense shaking table.However,the applicability of the safety assessment system for reinforced concrete(RC)structures with complex hysteretic material nonlinearity has yet to be explored;the previous approach based on a simplified lumpedmass model with a Bouc-Wen hysteretic model does not accurately represent the inherent nonlinear behavior and resulting damage states of RC structures.This study extends the rapid building safety assessment system to low-rise RC moment resisting frame structures representing typical residential apartments in Japan.First,a safety classification for RC structures based on a damage index consistent with the current state of practice is defined.Then,a 3D nonlinear numerical model of a two-story moment frame structure is created.A simplified lumped-mass nonlinear model is developed and calibrated using the 3D model,incorporating the Takeda degradation model for the RC material nonlinearity.This model is used to simulate the seismic response and associated damage sensitive features(DSF)for random ground motion.The resulting database of responses is used to train a convolutional neural network(CNN)that performs rapid safety assessment.The developed system is validated using the 3D nonlinear analysis model subjected to historical earthquakes.The results indicate the applicability of the proposed system for RC structures following seismic events.

A Rhetorical Structure Theory Based Approach to Texture Coherence in Chinese EFL Learners' Argumentative Writing

Based on Rhetorical Structure Theory(RST),this study intends to investigate into the typical features of rhetorical relations in Chinese EFL learners’argumentative writing and their relationship with writing quality.A set of 60 essays(30 with the highest scores and another 30 with the lowest scores)were drawn from SWECCL(Spoken and Written English Corpus of Chinese Learners).These essays were then cut into elementary discourse units and manually annotated with rhetorical relations.Research findings show that there is no significant difference in terms of the total numbers and types of rhetorical relations between the two proficiency groups.However,comparisons of the rhetorical relations both at the intra-paragraph and at the inter-paragraph level indicate statistical differences between the two groups.

基于改进TextRank的科技文本关键词抽取方法

针对科技文本关键词抽取任务中抽取出现次数少但能较好表达文本主旨的词语效果差的问题,提出一种基于改进TextRank的关键词抽取方法。首先,利用词语的词频-逆文档频率(TF-IDF)统计特征和位置特征优化共现图中词语间的概率转移矩阵,通过迭代计算得到词语的初始得分;然后,利用K-Core(K-Core decomposition)算法挖掘KCore子图得到词语的层级特征,利用平均信息熵特征衡量词语的主题表征能力;最后,在词语初始得分的基础上融合层级特征和平均信息熵特征,从而确定关键词。实验结果表明,在公开数据集上,与TextRank方法和OTextRank(Optimized TextRank)方法相比,所提方法在抽取不同关键词数量的实验中,F1均值分别提高了6.5和3.3个百分点;在科技服务项目数据集上,与TextRank方法和OTextRank方法相比,所提方法在抽取不同关键词数量的实验中,F1均值分别提高了7.4和3.2个百分点。实验结果验证了所提方法抽取出现频率低但较好表达文本主旨关键词的有效性。

Automatic Persian Text Summarization Using Linguistic Features from Text Structure Analysis

With the remarkable growth of textual data sources in recent years,easy,fast,and accurate text processing has become a challenge with significant payoffs.Automatic text summarization is the process of compressing text documents into shorter summaries for easier review of its core contents,which must be done without losing important features and information.This paper introduces a new hybrid method for extractive text summarization with feature selection based on text structure.The major advantage of the proposed summarization method over previous systems is the modeling of text structure and relationship between entities in the input text,which improves the sentence feature selection process and leads to the generation of unambiguous,concise,consistent,and coherent summaries.The paper also presents the results of the evaluation of the proposed method based on precision and recall criteria.It is shown that the method produces summaries consisting of chains of sentences with the aforementioned characteristics from the original text.

Reactive adsorption of thiophene on Ni/ZnO adsorbent:Effect of ZnO textural structure on the desulfurization activity

To better understand the nature of reactive adsorption of thiophene on Ni/ZnO adsorbent,the effect of ZnO textural structure on the desulfurization activity was investigated.ZnO materials were synthesized by low-temperature solid-state reaction and the corresponding Ni/ZnO adsorbents were prepared by incipient impregnation method.The analysis results showed that the crystalline sizes of ZnO as-synthesized as well as the BET surface areas varied obviously with the calcination temperature.The activity evaluations indicated that the Ni/ZnO adsorbents prepared with ZnO possessed a favorable textural structure as active component exhibited good activity of removing thiophene.The evolutions of the main crystalline phases of Ni/ZnO adsorbents before and after reaction confirmed that ZnO played a crucial role in taking up S element and converting it into ZnS in the reactive adsorption process.It was concluded that ZnO with larger surface area and smaller crystal particles resulted in better desulfurization activity,which may be the main reason for the different activities of the Ni/ZnO adsorbents prepared with ZnO calcined at different temperatures.